The data lake may be all about Apache Hadoop, but integrating operational data can be a challenge. Learn how to deliver real-time feeds of transactional data from mainframes and distributed environments directly into Hadoop clusters and make constantly changing data more available.
Recently, I had the honor of speaking with a number of the world’s most influential thought-leaders in the fields of data science, data analytics, machine learning and digital transformation. This group of prominent data technologists was more than happy to answer a wide variety of question on
Nancy Hensley, director of offering management for IBM Analytics speaks with Rob Thomas, vice president of development for analytics, at IBM, on the subject of business transformation, leading to a discussion of the data maturity curve.
Is your organization stuck at the edge of Hadoop adoption, searching for a path to broad use that doesn’t hold back your most proficient users? Big data discovery technology aims to help you bridge the chasm between early adoption and majority use, bringing rank-and-file users into the fold without
Batch processing of big data often doesn’t provide the performance desired for interactive queries. Performance will depend on the type and volume of data being processed. When interactive exploration or analytics is needed, data staging with analytics-oriented, high-volume databases is needed.